A Review of Machine learning Use-Cases in Telecommunication Industry in the 5G Era

Mahmoud, Haitham and Ismail, Tawfik (2021) A Review of Machine learning Use-Cases in Telecommunication Industry in the 5G Era. In: 16th International Computer Engineering Conference (ICENCO), 29th - 30th December 2020, Cairo, Egypt.

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With the development of the 5G and Internet of things (IoT) applications, which lead to an enormous amount of data, the need for efficient data-driven algorithms has become crucial. Security concerns are therefore expected to be raised using state-of-the-art information technology (IT) as data may be vulnerable to remote attacks. As a result, this paper provides a high-level overview of machine-learning use-cases for data-driven, maintaining security, or easing telecommunications operating processes. It emphasizes the importance of analyzing the role of machine learning in the telecommunications sector in terms of network operation.

Item Type: Conference or Workshop Item (Paper)
Identification Number: https://doi.org/10.1109/ICENCO49778.2020.9357376
1 December 2020Accepted
24 February 2021Published Online
Uncontrolled Keywords: Machine-learning, Telecommunications industry, Artificial intelligence
Subjects: CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science
Divisions: Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology
Depositing User: Gemma Tonks
Date Deposited: 13 Nov 2023 16:43
Last Modified: 13 Nov 2023 16:43
URI: https://www.open-access.bcu.ac.uk/id/eprint/14933

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